Quantitative Modeler (Python), Aladdin Financial Engineering, Vice President

Role Overview: You are being hired as a quantitative modeler to join the Portfolio Risk Modeling team at BlackRock. Your responsibilities will include building and maintaining risk models and analytics for various asset classes such as fixed income, equity, and private markets. These models are essential for risk management, portfolio construction, regulatory reporting, compliance, and performance attribution. Your role will involve utilizing sophisticated econometric/statistical methods and collaborating with traders, portfolio managers, and risk managers. Key Responsibilities: - Contribute to governance for Aladdin portfolio risk models including equities, fixed income, commodities, derivatives, etc. - Build and maintain model governance controls, including model performance monitoring, documentation, remediations, and support internal & external client model validations. - Communicate with internal stakeholders and external clients on model performance regularly, investigate exceptional model performance, diagnose issues, and conduct corrective remediations. - Coordinate with multiple teams and stakeholders while managing timelines. - Backtest, document, and guide new models and methodologies through validation. - Partner with engineering teams to integrate portfolio risk models into state-of-art production systems. Qualifications: - 7-9 years of experience in a quantitative field/statistical modeling, with a preference for experience in portfolio risk analytics and/or model governance. - Degree in a quantitative discipline (masters degree in finance/economics/statistics/financial engineering/math finance/engineering). - Knowledge of investments, portfolio management, econometrics, and empirical asset pricing. - Solid foundation in quantitative techniques. - Hands-on experience with statistical software (Python) and strong programming background. Intermediate to advanced proficiency in Python is preferred. - Experience with data handling, building and back-testing statistical and econometric models, and working in financial modeling or data science. - Ability to work effectively in a team, strong time and project management skills, track record of guiding junior talent, positive attitude, excellent communication, and presentation skills. Note: Omitting the additional details about the company as it is not directly related to the job description. Role Overview: You are being hired as a quantitative modeler to join the Portfolio Risk Modeling team at BlackRock. Your responsibilities will include building and maintaining risk models and analytics for various asset classes such as fixed income, equity, and private markets. These models are essential for risk management, portfolio construction, regulatory reporting, compliance, and performance attribution. Your role will involve utilizing sophisticated econometric/statistical methods and collaborating with traders, portfolio managers, and risk managers. Key Responsibilities: - Contribute to governance for Aladdin portfolio risk models including equities, fixed income, commodities, derivatives, etc. - Build and maintain model governance controls, including model performance monitoring, documentation, remediations, and support internal & external client model validations. - Communicate with internal stakeholders and external clients on model performance regularly, investigate exceptional model performance, diagnose issues, and conduct corrective remediations. - Coordinate with multiple teams and stakeholders while managing timelines. - Backtest, document, and guide new models and methodologies through validation. - Partner with engineering teams to integrate portfolio risk models into state-of-art production systems. Qualifications: - 7-9 years of experience in a quantitative field/statistical modeling, with a preference for experience in portfolio risk analytics and/or model governance. - Degree in a quantitative discipline (masters degree in finance/economics/statistics/financial engineering/math finance/engineering). - Knowledge of investments, portfolio management, econometrics, and empirical asset pricing. - Solid foundation in quantitative techniques. - Hands-on experience with statistical software (Python) and strong programming background. Intermediate to advanced proficiency in Python is preferred. - Experience with data handling, building and back-testing statistical and econometric models, and working in financial modeling or data science. - Ability to work effectively in a team, strong time and project management skills, track record of guiding junior talent, positive attitude, excellent communication, and presentation skills. Note: Omitting the additional details about the company as it is not directly related to the job description.